High-Efficiency Mitigation of Nonlinear Distortion in Microwave Photonics Link Assisted by Artificial Neural Network

Abstract

A microwave photonics radio over fiber link can deliver the radio frequency (RF) signal to realize the antenna remote. When the signal is a broadband and multicarrier RF signal, there are some linear distortions in the link, such as the crossmodulation distortion (XMD) and third-order intermodulation distortion (IMD3). It will destroy the wide-bandwidth performance of the link. Traditional postdigital compensation methods for XMD and IMD3 mitigation extract the baseband signal and reconstruct the compensation signal with calculated compensation factor. Here, a kind of artificial neural network genetic algorithm (ANN-GA) distortion compensation technique is proposed to seek the compensation factor instead of calculations. The neural network algorithm is used to fit the mapping function between the compensation factor and the distortion and give a set of predicted data as the original individual fitness value for the genetic algorithm. Based on the original value, the minimal distortion, the corresponding optimal compensation factors $\gamma$ and $\alpha$ are found with optimization iterations. Taking advantage of the optimal compensation factors, based on the traditional postdigital compensation method, the distortion is mitigated with a suppression ratio of -84.4 dB. In our paper, the mitigation technology of the XMD and IMD3 can be applied for any kinds of link instead of mathematically modelling the link and calculating the compensation factor. The technology can improve the intelligence and flexibility of microwave photonic link linearization design.